DataStax announced the technical achievement and general availability of Storage-Attached Indexing (SAI), fundamentally advancing indexing in Apache Cassandra™. Storage-Attached Indexing is a highly scalable, globally-distributed index for Apache Cassandra available on Astra and DataStax Enterprise (DSE).
Try Storage-Attached Indexing on Astra via the interactive scenario here.
DataStax has also opened a Cassandra Enhancement Proposal (CEP) with the Apache Cassandra project to share this with the open source community so all users of the popular, open source database can benefit.
Developers require a simple experience to leverage the power of Apache Cassandra for application development. Apache Cassandra is the proven open-source, NoSQL database of the internet’s largest applications and hardened by the world’s top enterprises.
Storage-Attached Indexing is a robust and powerful index in Apache Cassandra, making the open-source, scale-out, cloud-native NoSQL database more usable. With Storage-Attached Indexing, developers now have accessibility to familiar indexing and queries – such as WHERE clauses – in Apache Cassandra.
“Developers have typically faced a tradeoff between scalability, ease of use, and operations when choosing NoSQL,” said Ed Anuff, Chief Product Officer at DataStax. “Storage-Attached Indexing gives developers robust, new indexing that eliminates many of these tradeoffs, making development and data modeling in Apache Cassandra easier to use, while also increasing stability and performance and giving architects and operators fewer moving parts to manage.”
“Cassandra has proven itself to be a very fast and useful solution for us at GE Aviation. However, we have important use cases that require ad-hoc queries. To get around the current limitations, we have been using Solr with variable success. We are very excited about SAI. It has the potential to eliminate a huge pain point for us. It will further help the adoption of Cassandra and generally make the lives of many developers easier. This is definitely a step in the right direction for Cassandra,” said Julian Chultarsky, Principal Enterprise Applications Engineer at GE Aviation.
Storage-Attached Indexing is an index implementation that enables users to index multiple columns on the same table without scaling issues. It is optimized for storage and helps with Apache Cassandra performance and provides operational simplicity.
The benefits of Storage-Attached Indexing include:
- Improved stability
- Significantly reduces disk usage
- Improved numeric range performance
- Releases constraints to data modeling and barriers to scale-out
- Features modern and expected indexing features on Apache Cassandra
Storage-Attached Indexing is generally available in Astra and DSE 6.8.3. DataStax has also opened a Cassandra Enhancement Proposal (CEP) with the Apache Cassandra project.
Click to Tweet: Hello Storage-Attached Indexing! New indexing for @Cassandra, making the #opensource #scaleout #cloudnative #NoSQL #database easier for #developers to use w/ familiar indexing & queries in #Cassandra. Try it on Astra: https://dtsx.io/350hZj0
DataStax Blog: Better Cassandra Indexes for a Better Data Model
DataStax Astra: Cloud-Native Cassandra-as-a-Service
DataStax Enterprise: Scale-out data infrastructure for enterprises that need to handle any workload in any cloud
Open Life Blog: RUM Conjecture for Beginners
Webinar: Introduction to Astra: Cassandra-as-a-Service on Google Cloud
Documentation: Storage-Attached Indexing
Interactive Scenario: Storage-Attached Indexing on Astra
DataStax is the company behind the massively scalable, highly available, cloud-native NoSQL data platform built on Apache Cassandra™. DataStax gives users and enterprises the freedom to run data in any cloud at a global scale with zero downtime and zero lock-in. More than 450 of the world’s leading enterprises including Capital One, Cisco, Comcast, Delta Airlines, eBay, Macy’s, McDonald’s, Safeway, Sony, and Walmart use DataStax to build transformational data architectures for real-world outcomes. For more, visit DataStax.com and @DataStax.
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